The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Information about a digital image, such as the location and shape of particular objects in the digital image, may be extracted by performing segmentation upon the digital image. Image segmentation is a process for partitioning the digital image into a plurality of different regions. For example, a manufacturer or provider of a custom product, such as Zazzle, Inc., may wish to extract the location and shape of markup imprinted on a product for purposes of understanding the geometry of the custom product, such as a clothing item or accessory, when worn.
One approach for image segmentation is to transform the full-color representation of an image into a monochrome luminance image where the shade of each of pixel represents the luminance value of the pixel in the original image. Region partitions may be determined based on the luminance of pixels within the image. However, such an approach often produces inaccurate results since some of the color information necessary to determine accurate region partitions is lost in the transformation to the monochrome luminance image. Approaches for improved recognition of image partitions in images of marked up products are needed.